English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Recent work suggests improving the performance of Bloom filter byincorporating a machine learning model as a binary classifier. However, suchlearned Bloom filter does not take full advantage of the predicted probabilityscores. We proposed new algorithms that generalize the learned Bloom filter byusing the complete spectrum of the scores regions. We proved our algorithmshave lower False Positive Rate (FPR) and memory usage compared with theexisting approaches to learned Bloom filter. We also demonstrated the improvedperformance of our algorithms on real-world datasets.

Adaptive Learned Bloom Filter (Ada-BF): Efficient Utilization of the Classifier